A207 CLONAL PATTERNS BETWEEN POUCH NEOPLASIA AND PRIOR COLORECTAL NEOPLASIA IN INFLAMMATORY BOWEL DISEASE PATIENTS: AN EXPLORATORY COHORT STUDY
Bibliographic record
Abstract
Abstract Background Inflammatory bowel disease (IBD) patients with an ileo-anal pouch anastomosis (IPAA) bear an increased risk of pouch neoplasia, with prior colorectal neoplasia as the strongest predictor. It is unknown if pouch neoplasia develops independently or is derived from prior colorectal neoplasia. Purpose We aimed to assess potential clonality between prior colorectal neoplasia and pouch neoplasia in IPAA patients with IBD. Method In this explorative study we used the Dutch Nationwide Pathology Databank to identify IBD patients with both pouch neoplasia and colorectal neoplasia prior to colectomy. Clonality was assessed on colonic tissue of the lesion with shallow whole genome sequencing based copy number aberration (CNA) analysis and validated with immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). Result(s) We included 13 patients who fulfilled the inclusion criteria. Three patients showed matching clonality CNA profiles between prior colorectal neoplasia and pouch neoplasia, validated with matching IHC and FISH for p19 and HER2. Patients with matching clonal samples also showed on retrospective review concordant histology of the neoplastic lesion pre- and post IPAA, positive resection margins, metastasized disease or a short interval (<2 years) between colorectal and pouch neoplasia diagnoses. Image Conclusion(s) Three patients showed matching clonality patterns of neoplastic lesions, confirmed by clinical and histological data. Most pouch neoplasia in our cohort were molecularly different from their prior colorectal neoplasia. CNA provides a feasible method for clonality assessment in patients with colorectal neoplasia and subsequent pouch neoplasia. Disclosure of Interest None Declared
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".